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                        <li class="list-group-item d-flex justify-content-between align-items-start list-item-flex">
                            <div class="ms-2 me-auto paper-main">
                                <div class="fw-bold"> Differentially Private Diffusion Models Generate Useful Synthetic Images  </div>
                                <div> Sahra Ghalebikesabi, Leonard Berrada, Sven Gowal, Ira Ktena, Robert Stanforth, Jamie Hayes, Soham De, Samuel L. Smith, Olivia Wiles, Borja Balle </div>
                                <div>
                                        arXiv 2023.

                                        <a href="https://arxiv.org/abs/2302.13861"
                                           class="link-primary">Paper</a> &nbsp
                                </div>
                                <div class="paper-date-inner">2023-02-27</div>
                            </div>
                            <div class="paper-date">2023-02-27</div>
                        </li>
                        <li class="list-group-item d-flex justify-content-between align-items-start list-item-flex">
                            <div class="ms-2 me-auto paper-main">
                                <div class="fw-bold"> Data Forensics in Diffusion Models: A Systematic Analysis of Membership Privacy  </div>
                                <div> Derui Zhu<sup>1</sup>, Dingfan Chen<sup>1</sup>, Jens Grossklags, Mario Fritz </div>
                                <div>
                                        arXiv 2023.

                                        <a href="https://arxiv.org/abs/2302.07801"
                                           class="link-primary">Paper</a> &nbsp
                                </div>
                                <div class="paper-date-inner">2023-02-15</div>
                            </div>
                            <div class="paper-date">2023-02-15</div>
                        </li>
                        <li class="list-group-item d-flex justify-content-between align-items-start list-item-flex">
                            <div class="ms-2 me-auto paper-main">
                                <div class="fw-bold"> Raising the Cost of Malicious AI-Powered Image Editing  </div>
                                <div> Hadi Salman, Alaa Khaddaj, Guillaume Leclerc, Andrew Ilyas, Aleksander Madry </div>
                                <div>
                                        arXiv 2023.

                                        <a href="https://arxiv.org/abs/2302.06588"
                                           class="link-primary">Paper</a> &nbsp
                                </div>
                                <div class="paper-date-inner">2023-02-13</div>
                            </div>
                            <div class="paper-date">2023-02-13</div>
                        </li>
                        <li class="list-group-item d-flex justify-content-between align-items-start list-item-flex">
                            <div class="ms-2 me-auto paper-main">
                                <div class="fw-bold"> Better Diffusion Models Further Improve Adversarial Training  </div>
                                <div> Zekai Wang<sup>1</sup>, Tianyu Pang<sup>1</sup>, Chao Du, Min Lin, Weiwei Liu, Shuicheng Yan </div>
                                <div>
                                        arXiv 2023.

                                        <a href="https://arxiv.org/abs/2302.04638"
                                           class="link-primary">Paper</a> &nbsp
                                        <a href="https://github.com/wzekai99/DM-Improves-AT"
                                           class="link-primary">Github</a> &nbsp
                                </div>
                                <div class="paper-date-inner">2023-02-09</div>
                            </div>
                            <div class="paper-date">2023-02-09</div>
                        </li>
                        <li class="list-group-item d-flex justify-content-between align-items-start list-item-flex">
                            <div class="ms-2 me-auto paper-main">
                                <div class="fw-bold"> Adversarial Example Does Good: Preventing Painting Imitation from Diffusion Models via Adversarial Examples  </div>
                                <div> Chumeng Liang<sup>1</sup>, Xiaoyu Wu<sup>1</sup>, Yang Hua, Jiaru Zhang, Yiming Xue, Tao Song, Zhengui Xue, Ruhui Ma, Haibing Guan </div>
                                <div>
                                        arXiv 2023.

                                        <a href="https://arxiv.org/abs/2302.04578"
                                           class="link-primary">Paper</a> &nbsp
                                </div>
                                <div class="paper-date-inner">2023-02-09</div>
                            </div>
                            <div class="paper-date">2023-02-09</div>
                        </li>
                        <li class="list-group-item d-flex justify-content-between align-items-start list-item-flex">
                            <div class="ms-2 me-auto paper-main">
                                <div class="fw-bold"> Membership Inference Attacks against Diffusion Models  </div>
                                <div> Tomoya Matsumoto, Takayuki Miura, Naoto Yanai </div>
                                <div>
                                        arXiv 2023.

                                        <a href="https://arxiv.org/abs/2302.03262"
                                           class="link-primary">Paper</a> &nbsp
                                </div>
                                <div class="paper-date-inner">2023-02-07</div>
                            </div>
                            <div class="paper-date">2023-02-07</div>
                        </li>
                        <li class="list-group-item d-flex justify-content-between align-items-start list-item-flex">
                            <div class="ms-2 me-auto paper-main">
                                <div class="fw-bold"> MorDIFF: Recognition Vulnerability and Attack Detectability of Face Morphing Attacks Created by Diffusion Autoencoders  </div>
                                <div> Naser Damer, Meiling Fang, Patrick Siebke, Jan Niklas Kolf, Marco Huber, Fadi Boutros </div>
                                <div>
                                        arXiv 2023.

                                        <a href="https://arxiv.org/abs/2302.01843"
                                           class="link-primary">Paper</a> &nbsp
                                </div>
                                <div class="paper-date-inner">2023-02-03</div>
                            </div>
                            <div class="paper-date">2023-02-03</div>
                        </li>
                        <li class="list-group-item d-flex justify-content-between align-items-start list-item-flex">
                            <div class="ms-2 me-auto paper-main">
                                <div class="fw-bold"> Are Diffusion Models Vulnerable to Membership Inference Attacks?  </div>
                                <div> Jinhao Duan, Fei Kong, Shiqi Wang, Xiaoshuang Shi, Kaidi Xu </div>
                                <div>
                                        arXiv 2023.

                                        <a href="https://arxiv.org/abs/2302.01316"
                                           class="link-primary">Paper</a> &nbsp
                                </div>
                                <div class="paper-date-inner">2023-02-02</div>
                            </div>
                            <div class="paper-date">2023-02-02</div>
                        </li>
                        <li class="list-group-item d-flex justify-content-between align-items-start list-item-flex">
                            <div class="ms-2 me-auto paper-main">
                                <div class="fw-bold"> Extracting Training Data from Diffusion Models  </div>
                                <div> Nicholas Carlini<sup>1</sup>, Jamie Hayes<sup>1</sup>, Milad Nasr<sup>1</sup>, Matthew Jagielski, Vikash Sehwag, Florian Tramèr, Borja Balle, Daphne Ippolito, Eric Wallace </div>
                                <div>
                                        arXiv 2023.

                                        <a href="https://arxiv.org/abs/2302.00860"
                                           class="link-primary">Paper</a> &nbsp
                                </div>
                                <div class="paper-date-inner">2023-02-02</div>
                            </div>
                            <div class="paper-date">2023-02-02</div>
                        </li>
                        <li class="list-group-item d-flex justify-content-between align-items-start list-item-flex">
                            <div class="ms-2 me-auto paper-main">
                                <div class="fw-bold"> Salient Conditional Diffusion for Defending Against Backdoor Attacks  </div>
                                <div> Brandon B. May<sup>1</sup>, N. Joseph Tatro<sup>1</sup>, Piyush Kumar, Nathan Shnidman </div>
                                <div>
                                        arXiv 2023.

                                        <a href="https://arxiv.org/abs/2301.13721"
                                           class="link-primary">Paper</a> &nbsp
                                </div>
                                <div class="paper-date-inner">2023-01-31</div>
                            </div>
                            <div class="paper-date">2023-01-31</div>
                        </li>
                        <li class="list-group-item d-flex justify-content-between align-items-start list-item-flex">
                            <div class="ms-2 me-auto paper-main">
                                <div class="fw-bold"> Extracting Training Data from Diffusion Models  </div>
                                <div> Nicholas Carlini<sup>1</sup>, Jamie Hayes<sup>1</sup>, Milad Nasr<sup>1</sup>, Matthew Jagielski, Vikash Sehwag, Florian Tramèr, Borja Balle, Daphne Ippolito, Eric Wallace </div>
                                <div>
                                        arXiv 2023.

                                        <a href="https://arxiv.org/abs/2301.13188"
                                           class="link-primary">Paper</a> &nbsp
                                </div>
                                <div class="paper-date-inner">2023-01-30</div>
                            </div>
                            <div class="paper-date">2023-01-30</div>
                        </li>
                        <li class="list-group-item d-flex justify-content-between align-items-start list-item-flex">
                            <div class="ms-2 me-auto paper-main">
                                <div class="fw-bold"> Membership Inference of Diffusion Models  </div>
                                <div> Hailong Hu, Jun Pang </div>
                                <div>
                                        arXiv 2023.

                                        <a href="https://arxiv.org/abs/2301.09956"
                                           class="link-primary">Paper</a> &nbsp
                                </div>
                                <div class="paper-date-inner">2023-01-24</div>
                            </div>
                            <div class="paper-date">2023-01-24</div>
                        </li>
                        <li class="list-group-item d-flex justify-content-between align-items-start list-item-flex">
                            <div class="ms-2 me-auto paper-main">
                                <div class="fw-bold"> Denoising Diffusion Probabilistic Models as a Defense against Adversarial Attacks  </div>
                                <div> Lars Lien Ankile, Anna Midgley, Sebastian Weisshaar </div>
                                <div>
                                        arXiv 2023.

                                        <a href="https://arxiv.org/abs/2301.06871"
                                           class="link-primary">Paper</a> &nbsp
                                        <a href="https://github.com/ankile/Adversarial-Diffusion"
                                           class="link-primary">Github</a> &nbsp
                                </div>
                                <div class="paper-date-inner">2023-01-17</div>
                            </div>
                            <div class="paper-date">2023-01-17</div>
                        </li>
                        <li class="list-group-item d-flex justify-content-between align-items-start list-item-flex">
                            <div class="ms-2 me-auto paper-main">
                                <div class="fw-bold"> DensePure: Understanding Diffusion Models towards Adversarial Robustness  </div>
                                <div> Chaowei Xiao<sup>1</sup>, Zhongzhu Chen<sup>1</sup>, Kun Jin<sup>1</sup>, Jiongxiao Wang<sup>1</sup>, Weili Nie, Mingyan Liu, Anima Anandkumar, Bo Li, Dawn Song </div>
                                <div>
                                        NeurIPS 2022.

                                        <a href="https://arxiv.org/abs/2211.00322"
                                           class="link-primary">Paper</a> &nbsp
                                </div>
                                <div class="paper-date-inner">2022-11-01</div>
                            </div>
                            <div class="paper-date">2022-11-01</div>
                        </li>
                        <li class="list-group-item d-flex justify-content-between align-items-start list-item-flex">
                            <div class="ms-2 me-auto paper-main">
                                <div class="fw-bold"> Differentially Private Diffusion Models  </div>
                                <div> Tim Dockhorn, Tianshi Cao, Arash Vahdat, Karsten Kreis </div>
                                <div>
                                        arXiv 2022.

                                        <a href="https://arxiv.org/abs/2210.09929"
                                           class="link-primary">Paper</a> &nbsp
                                        <a href="https://nv-tlabs.github.io/DPDM/"
                                           class="link-primary">Project</a> &nbsp
                                </div>
                                <div class="paper-date-inner">2022-10-18</div>
                            </div>
                            <div class="paper-date">2022-10-18</div>
                        </li>
                        <li class="list-group-item d-flex justify-content-between align-items-start list-item-flex">
                            <div class="ms-2 me-auto paper-main">
                                <div class="fw-bold"> Improving Adversarial Robustness by Contrastive Guided Diffusion Process  </div>
                                <div> Yidong Ouyang, Liyan Xie, Guang Cheng </div>
                                <div>
                                        arXiv 2022.

                                        <a href="https://arxiv.org/abs/2210.09643"
                                           class="link-primary">Paper</a> &nbsp
                                </div>
                                <div class="paper-date-inner">2022-10-18</div>
                            </div>
                            <div class="paper-date">2022-10-18</div>
                        </li>
                        <li class="list-group-item d-flex justify-content-between align-items-start list-item-flex">
                            <div class="ms-2 me-auto paper-main">
                                <div class="fw-bold"> Fight Fire With Fire: Reversing Skin Adversarial Examples by Multiscale Diffusive and Denoising Aggregation Mechanism  </div>
                                <div> Yongwei Wang<sup>1</sup>, Yuan Li<sup>1</sup>, Zhiqi Shen </div>
                                <div>
                                        arXiv 2022.

                                        <a href="https://arxiv.org/abs/2208.10373"
                                           class="link-primary">Paper</a> &nbsp
                                </div>
                                <div class="paper-date-inner">2022-08-22</div>
                            </div>
                            <div class="paper-date">2022-08-22</div>
                        </li>
                        <li class="list-group-item d-flex justify-content-between align-items-start list-item-flex">
                            <div class="ms-2 me-auto paper-main">
                                <div class="fw-bold"> PointDP: Diffusion-driven Purification against Adversarial Attacks on 3D Point Cloud Recognition  </div>
                                <div> Jiachen Sun, Weili Nie, Zhiding Yu, Z. Morley Mao, Chaowei Xiao </div>
                                <div>
                                        arXiv 2022.

                                        <a href="https://arxiv.org/abs/2208.09801"
                                           class="link-primary">Paper</a> &nbsp
                                </div>
                                <div class="paper-date-inner">2022-08-21</div>
                            </div>
                            <div class="paper-date">2022-08-21</div>
                        </li>
                        <li class="list-group-item d-flex justify-content-between align-items-start list-item-flex">
                            <div class="ms-2 me-auto paper-main">
                                <div class="fw-bold"> Threat Model-Agnostic Adversarial Defense using Diffusion Models  </div>
                                <div> Tsachi Blau, Roy Ganz, Bahjat Kawar, Alex Bronstein, Michael Elad </div>
                                <div>
                                        arXiv 2022.

                                        <a href="https://arxiv.org/abs/2207.08089"
                                           class="link-primary">Paper</a> &nbsp
                                </div>
                                <div class="paper-date-inner">2022-07-17</div>
                            </div>
                            <div class="paper-date">2022-07-17</div>
                        </li>
                        <li class="list-group-item d-flex justify-content-between align-items-start list-item-flex">
                            <div class="ms-2 me-auto paper-main">
                                <div class="fw-bold"> Back to the Source: Diffusion-Driven Test-Time Adaptation  </div>
                                <div> Jin Gao<sup>1</sup>, Jialing Zhang<sup>1</sup>, Xihui Liu, Trevor Darrell, Evan Shelhamer, Dequan Wang </div>
                                <div>
                                        arXiv 2022.

                                        <a href="https://arxiv.org/abs/2207.03442"
                                           class="link-primary">Paper</a> &nbsp
                                </div>
                                <div class="paper-date-inner">2022-07-07</div>
                            </div>
                            <div class="paper-date">2022-07-07</div>
                        </li>
                        <li class="list-group-item d-flex justify-content-between align-items-start list-item-flex">
                            <div class="ms-2 me-auto paper-main">
                                <div class="fw-bold"> (Certified!!) Adversarial Robustness for Free!  </div>
                                <div> Nicholas Carlini, Florian Tramer, Krishnamurthy (Dj)Dvijotham, J. Zico Kolter </div>
                                <div>
                                        arXiv 2022.

                                        <a href="https://arxiv.org/abs/2206.10550"
                                           class="link-primary">Paper</a> &nbsp
                                </div>
                                <div class="paper-date-inner">2022-06-21</div>
                            </div>
                            <div class="paper-date">2022-06-21</div>
                        </li>
                        <li class="list-group-item d-flex justify-content-between align-items-start list-item-flex">
                            <div class="ms-2 me-auto paper-main">
                                <div class="fw-bold"> Guided Diffusion Model for Adversarial Purification from Random Noise  </div>
                                <div> Quanlin Wu, Hang Ye, Yuntian Gu </div>
                                <div>
                                        arXiv 2022.

                                        <a href="https://arxiv.org/abs/2206.10875"
                                           class="link-primary">Paper</a> &nbsp
                                </div>
                                <div class="paper-date-inner">2022-06-17</div>
                            </div>
                            <div class="paper-date">2022-06-17</div>
                        </li>
                        <li class="list-group-item d-flex justify-content-between align-items-start list-item-flex">
                            <div class="ms-2 me-auto paper-main">
                                <div class="fw-bold"> Guided Diffusion Model for Adversarial Purification  </div>
                                <div> Jinyi Wang<sup>1</sup>, Zhaoyang Lyu<sup>1</sup>, Dahua Lin, Bo Dai, Hongfei Fu </div>
                                <div>
                                        ICML 2022.

                                        <a href="https://arxiv.org/abs/2205.14969"
                                           class="link-primary">Paper</a> &nbsp
                                        <a href="https://github.com/jinyiw/guideddiffusionpur"
                                           class="link-primary">Github</a> &nbsp
                                </div>
                                <div class="paper-date-inner">2022-05-30</div>
                            </div>
                            <div class="paper-date">2022-05-30</div>
                        </li>
                        <li class="list-group-item d-flex justify-content-between align-items-start list-item-flex">
                            <div class="ms-2 me-auto paper-main">
                                <div class="fw-bold"> Diffusion Models for Adversarial Purification  </div>
                                <div> Weili Nie, Brandon Guo, Yujia Huang, Chaowei Xiao, Arash Vahdat, Anima Anandkumar </div>
                                <div>
                                        ICML 2022.

                                        <a href="https://arxiv.org/abs/2205.07460"
                                           class="link-primary">Paper</a> &nbsp
                                        <a href="https://diffpure.github.io/"
                                           class="link-primary">Project</a> &nbsp
                                        <a href="https://github.com/NVlabs/DiffPure"
                                           class="link-primary">Github</a> &nbsp
                                </div>
                                <div class="paper-date-inner">2022-05-16</div>
                            </div>
                            <div class="paper-date">2022-05-16</div>
                        </li>
                        <li class="list-group-item d-flex justify-content-between align-items-start list-item-flex">
                            <div class="ms-2 me-auto paper-main">
                                <div class="fw-bold"> TFDPM: Attack detection for cyber-physical systems with diffusion probabilistic models  </div>
                                <div> Tijin Yan, Tong Zhou, Yufeng Zhan, Yuanqing Xia </div>
                                <div>
                                        arXiv 2021.

                                        <a href="https://arxiv.org/abs/2112.10774"
                                           class="link-primary">Paper</a> &nbsp
                                </div>
                                <div class="paper-date-inner">2021-12-20</div>
                            </div>
                            <div class="paper-date">2021-12-20</div>
                        </li>
                        <li class="list-group-item d-flex justify-content-between align-items-start list-item-flex">
                            <div class="ms-2 me-auto paper-main">
                                <div class="fw-bold"> Adversarial purification with Score-based generative models  </div>
                                <div> Jongmin Yoon, Sung Ju Hwang, Juho Lee </div>
                                <div>
                                        ICML 2021.

                                        <a href="https://arxiv.org/abs/2106.06041"
                                           class="link-primary">Paper</a> &nbsp
                                        <a href="https://github.com/jmyoon1/adp"
                                           class="link-primary">Github</a> &nbsp
                                </div>
                                <div class="paper-date-inner">2021-06-11</div>
                            </div>
                            <div class="paper-date">2021-06-11</div>
                        </li>
                </ol>
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